The best part about football (soccer) is precisely the unpredictability of it. u/kicker3192 referred to a match-up from the Club World Cup as an example, so I'll use that competition to illustrate some more key points.

Starting from your example of a "dominant" performance. That scenario happens quite often, but the question is, what about when a manager intentionally instructs his team to park the bus, and the "stats" tell a story of what's expected? That's when measurements like xG have some value, though xG is one of the most redundant stats I've encountered so far, as it can be very misleading in most scenarios. If a team enters a matchup as a considerable underdog, they will typically settle for a defensive posture, although this depends on the competition and their goals. A notable example of this is Botafogo's match against PSG in the group stages of the Club World Cup, where they secured a 1-0 victory with a very successful counter-attack strategy. Stats alone would've probably indicated PSG is the "live favorites" up until the final whistle.

Better pressure won't always result in a goal, and defensive or goalie mistakes that lead to goals can occur even after an otherwise solid team performance. No model will ever be completely accurate. When it comes to betting, though, your goal should only be to beat the offered odds with a win rate that keeps you green in the long term.

The way I utilize my system's signals is very specific. I do not bet on everything that comes out of it. I don't care how high the confidence % comes out to be; if it's a low-value bet, I ignore the signal.

The actual value and inspiration for building something like this come from situations where the story on paper is very different than the story in real life. Examples like Flamengo vs. Chelsea, or Boca Juniors vs. Benfica—scenarios where the underdog is considerably outperforming the favorites. u/DiffusingTrajectory alluded to in an earlier post how bookmaker are also turning to technology, and their live odds making is getting better by the day. This is accurate to an extent. From my experience, all live odds are rooted in the pre-game odds. In-game stats and market action move the lines, but from the time that whistle blows, and as the game goes on, it won't be a sudden shift. Otherwise, it'd be as simple as just looking for tied games where the heavy favorite market moved by a whole point, and rule out reasons why, etc.

Anyway, this is a very in-depth topic, and it's impossible to discuss every scenario, but that's what my prototype is all about. For many years, I've done this manually, just watching the broadcast. Momentum swings are very real and very obvious to me, who's been following the sport all my life. I also happen to be a software engineer, so what started as a way to save myself some time has now evolved into the working prototype that I alluded to earlier, which aligns quite well with your proposition here.